As Marqeta’s Principal Security Engineer you will serve as the technical lead across our security engineering function. This role combines three critical responsibilities: leading product security engineering across our payment platform, building our AI security program as we scale generative AI and ML capabilities, and providing security architecture oversight across enterprise and infrastructure security.

Your primary focus will be product security and AI—threat modeling payment features, securing APIs, building genAI controls, and ensuring AI-powered capabilities ship securely. You'll also own the security architecture function and provide technical oversight for infrastructure security—endpoint protection, network security, VPN, and enterprise security controls—ensuring coherent security standards across everything we build and operate.

You'll partner closely with Product Security, Infrastructure Security, and Security Operations teams and serve as the security voice in our Model Risk Office. This is an individual contributor role with mentoring responsibilities and broad technical influence across the security, engineering, and business technology organizations.

We work Flexible First. This role can be performed remotely anywhere within the United States or from our Oakland office. We’d love for you to join us!

You'll have the chance to:

Lead product security engineering for our payment platform—owning threat modeling, security architecture review, secure SDLC practices, and API security across the engineering organization
Help mature our AI security programdeveloping genAI controls, securing ML pipelines, and working alongside the Model Risk Office for model evaluations.
Provide security architecture oversight across infrastructure and enterprise security—endpoint, network, VPN, and corporate security controls—ensuring technical standards are coherent across all security domains
Shape how security engineering scales across the organization through tooling, frameworks, security champions engagement, and engineering partnerships

The Impact You'll Have:

Product Security:

Conduct security architecture reviews and threat modeling for new product features, APIs, and service integrations across the payment platform
Define and maintain secure development lifecycle practices including secure code review standards, API security patterns, and authentication/authorization frameworks
Develop self-service security tooling and developer-facing guardrails that reduce friction while maintaining security posture

AI Security:

Lead security strategy and risk assessment for AI/ML systems including customer-facing AI products, fraud detection models, LLM integrations, and recommendation systems
Build genAI security controls—prompt injection prevention, output filtering, model validation, and monitoring frameworks
Perform security assessments of AI/ML model architectures, training pipelines, inference endpoints, and deployment infrastructure
Evaluate and operationalize AI-powered security tools (e.g., AI-assisted code review, anomaly detection, automated threat intelligence) to improve security operations

Enterprise & Infrastructure Security Oversight:

Provide technical oversight for infrastructure security including endpoint protection, network security, VPN, and enterprise security controls
Ensure coherent security architecture standards across product, cloud infrastructure, and corporate environments
Drive technical decisions for security tooling and controls that span the full environment—from developer laptops to production infrastructure

Across All Domains:

Partner across Product Security, Infrastructure Security, and Security Operations teams as well as engineering, data science, and compliance
Mentor security engineers and cross-functional teams, raising the organization's overall security engineering maturity
Communicate security risks and strategy to executive and board-level audiences

Who You Are:

10+ years of security engineering experience with demonstrated technical leadership across multiple security domains; or equivalent combination of education and experience
Deep product security expertise: threat modeling, security architecture review, secure code review, API security, authentication/authorization design, and secure SDLC practices
Experience with or strong interest in AI/ML security—understanding of risks including adversarial attacks, model poisoning, prompt injection, data privacy, and AI supply chain threats. We want someone who is genuinely excited about AI technology and wants to secure it, not just govern it
Broad security fluency across infrastructure and enterprise security—endpoint protection, network security, identity, and cloud security—even if your deepest expertise is in application and product security
Experience working in cloud-native environments (AWS preferred) with familiarity across AI/ML services (Bedrock, SageMaker, etc.)
Proven ability to build security frameworks, tools, and programs from the ground up
Strong programming skills in at least one language (Python, Java, Go, or similar) with the ability to read and review code across multiple languages
Experience with security assessment methodologies and risk management frameworks
Working knowledge of compliance and control frameworks relevant to financial services (PCI DSS, SOX, SOC2, NIST CSF)
Ability to communicate complex security risks to both technical and executive audiences

Nice to Have:

Financial services or fintech experience strongly preferred
Experience securing payment processing systems, card issuing platforms, fraud detection models, or transaction monitoring infrastructure
Hands-on experience with LLM security: prompt injection mitigation, output filtering, RAG security, agent security patterns
Experience with enterprise security platforms (EDR, SIEM, identity providers, network security tools)
Experience with ML frameworks (PyTorch, TensorFlow) or background in data science / machine learning engineering
Knowledge of AI governance, model risk management practices, and emerging AI regulatory frameworks (EU AI Act, NIST AI RMF)
Background in supply chain security, CI/CD pipeline security, or secure software composition analysis
Experience with privacy-preserving ML techniques (differential privacy, federated learning, secure multi-party computation)
Experience with Kubernetes, containerized workloads, and Infrastructure as Code (Terraform)
CISSP, CCSP, CISA, or other relevant security certifications
Experience building and scaling security programs in high-growth environments

Typical Process:

Application Submission
Recruiter phone call
Hiring manager video call
Virtual “Onsite” consisting of 5-6, 45-60 min video calls
Offer!

At this point, we hope you're feeling excited about the role. You're encouraged to apply even if your experience doesn't precisely match the job description. Your skills and passion will stand out—and set you apart—especially if your career has taken some extraordinary twists and turns. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates, so again, don’t hesitate to apply — we’d love to hear from you.

Compensation and Benefits:

Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office. To support Flex First, we calibrate pay to a competitive value according to working location. Compensation is aligned according to three tiers within the United States:

National: A baseline tier that applies to most of the geographic territory of the United States.
Premium: Slightly elevated from the National tier, and oriented toward a narrower set of higher cost-of-living areas, such as Los Angeles CA and Seattle WA
Premium Plus: A tier for the most expensive working areas, like the San Francisco Bay area and New York City.

Visit this page or consult with a Recruiter to determine which tier would be applicable to you.

When determining salaries, we consider several factors including, but not limited to, skills, prior experience, and work location. The new-hire base salary range for this position is:

National: $218,300 - $272,900
Premium: $236,200 - $295,300
Premium Plus: $256,800 - $321,000

We also believe in recognizing the contributions of our people. That's why we award annual bonuses to eligible employees, rewarding both individual performance and the success of the entire company.

Along with monetary compensation, Marqeta offers

Multiple health insurance options
Flexible time off – take what you need
Retirement savings program with company contribution and after tax contributions
Equity in a publicly-traded company and an Employee Stock Purchase Program
Family-forming benefits, fertility support, and up to 20 weeks of Parental Leave
Free therapy sessions, financial and professional coaching, and legal advice
Monthly stipend to support our remote work model
Annual “development dollars” to support our people growth and development
Through Flex First, the freedom to live and work wherever you and your family thrive

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